Simple Technical Trading Rules Research Articles

Are simple technical trading rules profitable in bitcoin markets?

This paper examines the profitability of simple technical trading rules in bitcoin markets comprehensively, by taking into account realistic investor behaviour and transaction costs, and data mining problems. Realistic investor behaviour is replicated by first employing 75,360 simple technical trading rules, divided over 6 commonly used trading rule classes and daily and intraday frequencies. Next, we select the best performing rules after transaction costs using a multiple hypothesis procedure. Finally, we form portfolios combining the selected rules and analyse their out-of-sample performance. We find that, especially risk–return wise, simple technical trading rules can outperform a buy-and-hold strategy in the bitcoin market out-of-sample.

Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information

This paper examines whether the 2007 - 2008 global financial crisis (GFC) played any role in changing the state of efficiency for the foreign exchange markets. For comparison purposes, I assess market efficiency based on the forward unbiasedness hypothesis (FUH) as well as the profitability of simple technical trading rules in the form of moving average, momentum, and relative strength index. A general finding from my comparative analysis (the FUH vis-à-vis technical trading rules) reveals that the GFC causes a time variation in the performance of currency markets, but both tests predict opposite conclusions on the direction of the change in the state of market performance. This evidence emphasizes the importance of qualifying the difference between fundamental and technical information when investigating the efficiency of foreign exchange markets.

Profitability of technical trading rules among cryptocurrencies with privacy function

This paper studies simple moving average trading strategies employing daily price data on the ten most-traded cryptocurrencies that exhibit the ‘privacy function’. Investigating the 2016–2018 period, our results indicate a variable moving average strategy is successful onlywhen applied to Dash generating returns of 14.6%−18.25% p.a. in excess of the simple buy-and-hold benchmark strategy. However, when applying our technical trading rules to the entire set of ten privacy coins shows that, on an aggregate level, simple technical trading rules do not generate positive returns in excess of a buy-and-hold strategy.

Market efficiency and technical analysis during different market phases: further evidence from Malaysia

The profitability of simple technical trading rules remains an interesting topic and has been thoroughly explored in the literature. In this paper, the authors investigate the profitability of two popular moving average (MA) rules in the Bursa Malaysia before, during and after the global financial crisis (GFC) of 2008-2009. Using variable length MA (VMA) and fixed length MA (FMA) technical rules, the authors explore if there were differences in their performance during the different market phases, and if swing traders can gain by trading on the basis of these strategies. When practical trading constraints are considered, the authors find that MA rules performed differently during the three market phases. Over time, the forecasting powers of these rules have diluted and they have performed poorly in the most recent subsample. The findings suggest that the Malaysian stock market is gradually becoming more efficient. This outcome can be attributed to the technological advancements and widespread use of exchange traded funds.

Profitability of simple technical trading rules of Chinese stock exchange indexes

Although technical trading rules have been widely used by practitioners in financial markets, their profitability still remains controversial. We here investigate the profitability of moving average (MA) and trading range break (TRB) rules by using the Shanghai Stock Exchange Composite Index (SHCI) from May 21, 1992 through December 31, 2013 and Shenzhen Stock Exchange Component Index (SZCI) from April 3, 1991 through December 31, 2013. The t-test is adopted to check whether the mean returns which are conditioned on the trading signals are significantly different from unconditioned returns and whether the mean returns conditioned on the buy signals are significantly different from the mean returns conditioned on the sell signals. We find that TRB rules outperform MA rules and short-term variable moving average (VMA) rules outperform long-term VMA rules. By applying White’s Reality Check test and accounting for the data snooping effects, we find that the best trading rule outperforms the buy-and-hold strategy when transaction costs are not taken into consideration. Once transaction costs are included, trading profits will be eliminated completely. Our analysis suggests that simple trading rules like MA and TRB cannot beat the standard buy-and-hold strategy for the Chinese stock exchange indexes.

Market Efficiency and Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in US markets and also compare the excess returns between US market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in US equity index after 1975. During the 1990's break-even costs turned to be negative, -0.06%, even failing to beat a buy-holding strategy in US equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.

Predictability of the simple technical trading rules: An out-of-sample test

In a true out-of-sample test based on fresh data we find no evidence that several well-known technical trading strategies predict stock markets over the period of 1987 to 2011. Our test safeguards against sample selection bias, data mining, hindsight bias, and other usual biases that may affect results in our field. We use the exact same technical trading rules that Brock, Lakonishok, and LeBaron (1992) showed to work best in their historical sample. Further analysis shows that this poor out-of-sample performance most likely is not due to the market becoming more efficient – instantaneously or gradually over time – but probably a result of bias.

Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets

This study investigates whether the moving average and trading range breakout rules can forecast stock price movements and outperform a simple buy-and-hold strategy after adjusting for transaction costs over the period from January 1991 to December 2008. The empirical results show that the trading rules have stronger predictive power in the emerging stock markets of Malaysia, Thailand, Indonesia, and the Philippines than in the more developed stock market of Singapore consistent with earlier studies. In addition, the short-term variants of the technical trading rules have better predictive ability than long-term variants. However, unlike earlier studies we show that transaction costs can eliminate the trading profits implying weak-form efficiency in most stock markets during our study period further suggesting that these markets have become more informationally efficient over time. Our results highlight the need to constantly revisit statements about the efficiency of economically dynamic and rapidly growing emerging stock markets.

Predictability of the Simple Technical Trading Rules: An Out-of-Sample Test

In a true out of sample test we find no evidence that several well-known technical trading strategies predict stock markets over the period of 1987 to 2011. Our test is free of the sample selection bias, data mining, hindsight bias, or any of the other usual biases that may affect results in our field. We use the exact same technical trading rules that Brock, Lakonishok and LeBaron (1992) showed to work best in their historical sample. Further analysis shows that this poor out-of-sample performance most likely is not due to the market becoming more efficient - instantaneously or gradually over time - but probably a result of bias.

Intertemporal profitability and the stability of technical analysis: evidences from the Hong Kong stock exchange

This study investigates the impact of market integration on the profitability of two simple and popular technical trading rules, the Simple Moving Average (SMA) and the Trading Range Break (TRB) in Hong Kong. Using data from 1972 to 2006, we find that the SMA (1, 50) consistently outperforms the market before the integration of stock exchanges in 1986. Under the (1, 50) rule, a variable length moving average performs better than the fixed length moving average rule by 2.5 to 5% (annual) before transaction costs because it includes the information of the first 9 days into investors’ decision. The results are robust to the out of sample tests for the validity of the profitability of the trading rules. The returns of the trading range break rules are insignificant over the 35-year span. Our results support the conjecture that stock market integration may lead to better information efficiency. The findings of significant pre-1986 profits and insignificant post-1986 profits, contradict previous findings that returns are predictable in Hong Kong, suggesting that the Hong Kong stock market may be weak-form efficient after 1986. Overall, our results suggest that technical analysis matters for asset pricing.

Are moving average trading rules profitable? Evidence from the European stock markets

This article examines the profitability of several simple technical trading rules for 16 European stock markets over the 1990 to 2006 period. Our results indicate that increasing moving average rules indeed have predictive power being able to discern recurring price patterns for profitable trading, even after accounting for the effects of data snooping bias. To assess the profitability of different technical trading rules and strategies, we adopt the White's (2000) Reality Check (RC) test that quantifies the data snooping bias and adjusts for its effects. Our empirical results also support the hypothesis that technical trading rules can outperform the buy and hold strategy after accounting for transaction costs.

Technical Analysis in the Foreign Exchange Market

This article introduces the subject of technical analysis in the foreign exchange market, with emphasis on its importance for questions of market efficiency. “Technicians” view their craft, the study of price patterns, as exploiting traders’ psychological regularities. The literature on technical analysis has established that simple technical trading rules on dollar exchange rates provided 15 years of positive, risk-adjusted returns during the 1970s and 80s before those returns were extinguished. More recently, more complex and less studied rules have produced more modest returns for a similar length of time. Conventional explanations that rely on risk adjustment and/or central bank intervention do not plausibly justify the observed excess returns from following simple technical trading rules. Psychological biases, however, could contribute to the profitability of these rules. We view the observed pattern of excess returns to technical trading rules as being consistent with an adaptive markets view of the world.

Indonesia's stock market: evolving role, growing efficiency

The banking sector traditionally dominated Indonesia's financial system, and until the 1990s the stock market remained of little significance. Re-opened in 1977 after two decades of inactivity, the stock exchange made little contribution to Indonesia's development until a series of reform and deregulation measures were implemented from December 1987. This study examines the evolving role of the stock market in the financial system, and analyses changes in its efficiency over time. We find that stock market activity grew markedly in importance relative to banking after the reforms began to take effect, gaining the ascendancy in 2004 and moving well ahead subsequently. One contributor to this success is improvement in efficiency. Using two simple technical trading rules, we demonstrate that the stock exchange secondary market has indeed become significantly more efficient over time.

Profitability of Technical Trading Rules on the Baltic Stock Markets

In this note we study whether simple technical trading rules are pro table on the three Baltic stock markets. To statistically assess our ndings we consider the conventional t-test and a block-bootstrap procedure. The two evaluation methods give conflicting results. The t-test supports some of the rules, while the block-bootstrap does not.

Application of Simple Technical Trading Rules to Swiss Stock Prices: Is it Profitable?

This paper tests if the use of trading rules based on the crossing of moving averages on Swiss stock prices yields proftable results. The use of bands and oscillators such as the relative strength index or the stochastic indicator is also investigated. These rules are tested on daily returns of the SBC General Index for the period 1969-1997. It is found that the most profitable rule is a double moving average with averages computed on one and five days. With this rule, an annual average return on the SBC Index of 24.30% is obtained compared to a buy-and-hold annual return of 6.25%.

Market Efficiency and Returns to Simple Technical Trading Rules: Further Evidence from U.S., U.K., Asian and Chinese Stock Markets

Tian, Wan and Guo (2002) explored the predictability and profitability of technical trading rules in markets with different efficiency levels; namely, the U.S. and China. In the case of the U.S. they found rules to have no predictability after 1975, whereas their results give support to technical trading rules having both predictability and profitability for the Chinese markets across the 1990's. The purpose of this paper is to extend the analysis of Tian et al. in two ways. First, to see if the conclusions extend to other markets – namely, the U.K., Hong Kong and Japan. Second, in the case of China, to examine whether the predictability and profitability of technical trading rules changed across the 1990's. On the basis of daily data Tian et al's results for the U.S. market are supported by the results for a number of the main developed markets where the technical trading rules had predictive ability during the 1970's that disappeared by the 1990's. Furthermore, the results suggest that while technical trading rules had short term predictive ability and profitability in the Chinese stock markets during the 1990's, this lessened as the decade progressed.

The predictive ability and profitability of technical trading rules: does company size matter?

In this paper we investigate the predictive ability and profitability of simple technical trading rules for different sizes of company. Our results suggest that technical trading rules have progressively higher predictive ability the smaller the size of the company, but are not profitable given transaction costs.

Learning to Predict Rationally When Beliefs are Heterogeneous

This paper develops an adaptive learning scheme for an asset market with heterogeneous traders who are characterized by linear mean-variance preferences. We introduce the concept of a perfect forecasting rule which generates rational expectations for fundamentalists in the presence of investors with possibly non-rational beliefs. When these non-rational investors base their decisions on simple technical trading rules, perfect forecasting rules are approximated by successively estimating the excess demand function from historical data. Conditions are given under which trajectories generated by this adaptive learning scheme converge to trajectories with rational expectations for fundamentalists.

Learning to predict rationally when beliefs are heterogeneous

This paper develops an adaptive learning scheme for an asset market with heterogeneous traders who are characterized by linear mean-variance preferences. We introduce the concept of a perfect forecasting rule which generates rational expectations for fundamentalists in the presence of investors with possibly non-rational beliefs. When these non-rational investors base their decisions on simple technical trading rules, perfect forecasting rules are approximated by successively estimating the excess demand function from historical data. Conditions are given under which trajectories generated by this adaptive learning scheme converge to trajectories with rational expectations for fundamentalists.

Are technical trading rules profitable? Evidence for head-and-shoulder rules

The profitability of chartist trading rules on foreign exchange markets is still under debate. Since simple technical trading rules may not adequately capture the complex phenomenon of chartist trading, this study focuses on the prominent head-and-shoulder pattern as a representative trading rule which incorporates various ‘technical’ ideas such as smoothed trends, trend reversal, resistance levels, and volatility clustering. For various combinations of the building blocks of head-and-shoulder definitions the result is generally negative: Returns to head-and-shoulder trading rules are not significantly positive - and if there is any evidence for non-zero returns at all, then it is evidence for negative returns.